metadata
library_name: transformers
tags:
- compression
- expert-merging
- moe
- code
- mlx
- mlx-my-repo
license: apache-2.0
base_model: bknyaz/Qwen3-Coder-Next-REAM
TomLucidor/Qwen3-Coder-Next-REAM-mlx-4Bit
The Model TomLucidor/Qwen3-Coder-Next-REAM-mlx-4Bit was converted to MLX format from bknyaz/Qwen3-Coder-Next-REAM using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("TomLucidor/Qwen3-Coder-Next-REAM-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)